OOS 4
Advances in Modeling Wildlife Abundance

Monday, August 10, 2015: 1:30 PM-5:00 PM
316, Baltimore Convention Center
Organizer:
Beth Gardner, North Carolina State University
Co-organizers:
Rahel Sollmann, North Carolina State University; and J. Andrew Royle, USGS Patuxent Wildlife Research Center
Moderator:
Beth Gardner, North Carolina State University
Estimating population size has been a key issue of interest for decades in ecological studies. In conservation and management, some of the most pressing questions are related to how climate change and habitat fragmentation will impact populations. One major step in answering these questions is understanding the spatial and temporal dynamics of abundance, as well as, habitat associations, density dependence, and resource selection. Methods, such as capture-recapture, mark-resight, distance sampling, and aerial counts, are commonly used to estimate abundance for mammals, reptiles, birds, insects, trees, etc. New techniques such as genetic sampling and camera trapping, along with enhanced computing capabilities, have spurred a wave of advances in statistical models for abundance estimation. These extensions include explicitly incorporating spatial and temporal information, combining multiple data sources, investigating community structure, etc. These new approaches allow researchers to not only estimate abundance, but to address other ecological questions related to variation of abundance in space and time, survival/recruitment, animal movement, resource selection, and patterns in community composition. Modeling procedures that allow researchers to gain a better understanding of these processes are invaluable. For example, camera trapping now allows researchers to photo-capture animals that are cryptic or rare, such as jaguars. In some species, individuals can be identified in photo-captures and new spatial capture-recapture models can be utilized to estimate population size, variation in movement between sexes, resource selection, survival and recruitment. Similarly, with the use of new N-mixture models, repeated count data can be used to estimate population size and trends without having to identify individuals. In this session, we aim to provide an overview over a broad range of advances in models for estimating population size based on traditional methodologies like distance sampling, capture-recapture, and count based surveys, but incorporating new technologies and data sources to address questions broader than just abundance. The models are widely applicable across many taxa, time scales, and spatial extents in ecology.
1:30 PM
 A community distance sampling model for estimating seabird abundance and distribution
Rahel Sollmann, North Carolina State University; Beth Gardner, North Carolina State University; Kathryn A. Williams, Biodiversity Research Institute; Andrew T. Gilbert, Biodiversity Research Institute; Richard R. Veit, College of Staten Island
1:50 PM
2:10 PM
 Estimating marine bird abundance in offshore wind development areas: Integrating uncertain species identification in transect surveys
Nathan J. Hostetter, North Carolina State University; Beth Gardner, North Carolina State University; Holly F. Goyert, North Carolina State University; Andrew T. Gilbert, Biodiversity Research Institute; Kathryn A. Williams, Biodiversity Research Institute; Emily E. Connelly, Biodiversity Research Institute; Melissa Duron, Biodiversity Research Institute; Richard R. Veit, College of Staten Island
2:50 PM
 Spatio-temporal N-mixture models for predicting metapopulation dynamics
Paige Howell, University of Georgia; Richard Chandler, University of Georgia; Erin Muths, USGS Fort Collins Science Center; Blake Hossack, USGS; Brent H. Sigafus, U.S. Geological Survey
3:10 PM
3:20 PM
3:40 PM
 Integrating citizen-science data with movement models to estimate raptor populations: A case study with golden eagles in eastern North America
Andrew J. Dennhardt, Michigan State University; Todd E. Katzner, USGS Forest and Rangeland Ecosystem Science Center; Adam E. Duerr, West Virginia University; David Brandes, Lafayette College
4:00 PM
 Modeling density in stratified populations using hierarchical spatial capture-recapture
Sarah J. Converse, USGS Patuxent Wildlife Research Center; J. Andrew Royle, USGS Patuxent Wildlife Research Center
4:20 PM
 Estimating abundance when landscape structure determines patterns of both space-use and density
Christopher Sutherland, Cornell University; Angela K. Fuller, New York Cooperative Fish and Wildlife Research Unit, Cornell University; J. Andrew Royle, USGS Patuxent Wildlife Research Center
4:40 PM
 Integrating spatial-capture recapture models into models of plague transmission in prairie dogs
Robin E. Russell, US Geological Survey; Tonie Rocke, US Geological Survey; Dan Walsh, US Geological Survey; Katie Richgels, University of Wisconsin